quantifier elimination via functional composition
DESCRIPTION
Quantifier Elimination via Functional Composition. Jie-Hong Roland Jiang Dept. of Electrical Eng. / Grad. Inst. of Electronics Eng. National Taiwan University Taipei 10617, Taiwan. Outline. Motivations Prior work Quantifier elimination by functional composition Propositional logic - PowerPoint PPT PresentationTRANSCRIPT
2009/6/30 CAV 2009 1
Quantifier Elimination via Functional Composition
Jie-Hong Roland Jiang
Dept. of Electrical Eng. / Grad. Inst. of Electronics Eng.National Taiwan UniversityTaipei 10617, Taiwan
2009/6/30 CAV 2009 2
Outline
Motivations
Prior work
Quantifier elimination by functional composition Propositional logic Predicate logic
Experimental results
Conclusions
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Introduction
Quantifier elimination transforms a quantified formula, e.g., x1x2x3 xn , into an equivalent quantifier-free formula can be preferable to x1x2x3 xn
E.g., Properties of can be reasoned more easily can be treated as a synthesis result for implementation
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Introduction
QE examplesGauss elimination for systems of linear equ
alities
Fourier-Motzkin elimination for systems of linear inequalities
Cylindrical algebraic decomposition for systems of polynomial inequalities
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Motivations
QE arises in many contexts, including computation theory, mathematical logic, optimization, …Constraint reductionQuantified Boolean Formula (QBF) solving
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Main focus
Propositional logicQuantifier elimination for QBFs
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Prior work
Formula expansion y (x,y) = (x,0) (x,1) BDD, AIG based image-computation [Coudert90][Pigorsch06]
Normal-form conversion Existential (universal) quantification is computationally trivial for disjunctive (c
onjunctive) normal form formulas Simply remove from the formula the literals of variables to be quantified
E.g., x1[(x1 x2 x3)(x1 x3)(x2 x4)] = (x2 x3)(x3)(x2 x4) Formula conversion between CNF and DNF [McMillan02]
Solution enumeration Compute (x) = y (x,y) by enumerating all satisfiable assignments on x SAT-based image computation, e.g., [Ganai04]
Yet another way?
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Question
Given a quantified formula y (x,y), what should a function f be such that (x,f(x)) = y (x,y)?
I.e., QE by functional composition
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Answer
(x,f(x)) = y (x,y) if and only if f has
care onset (x,1) (x,0) care offset (x,0) (x,1) don’t care set (x,1) (x,0)
In other words,((x,1) (x,0)) f ((x,0) (x,1))
Such f always exists
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Problem formulation
For universal quantification y (x,y) = y (x,y) = (x,f(x)) = (x,f(x)) f has
care onset (x,1) (x,0) care offset (x,0) (x,1) don’t care set (x,1) (x,0)
So by computing composite functions f, one can iteratively eliminate the quantifiers of any QBF
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Computation
f can be computed byBinary decision diagrams (BDDs)
Not scalable for large Craig interpolation
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Craig interpolation
(Propositional logic)
For A B unsatisfiable, there exists an interpolant of A w.r.t. B such that
1. A 2. B is unsatisfiable
3. refers only to the common variables of A and B
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Computation
A
care onsetB
care offset
interpolant
The interpolant is a valid implementation of f, which can be obtained from the refutation of A B in SAT solving and can be naturally represented in And-Inverter Graphs (AIGs)
care onset (x,1) (x,0) care offset (x,0) (x,1) don’t care set (x,1) (x,0)
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Composition vs. expansion
Is (x,f(x)) better than (x,0) (x,1) ?
f
x x
in terms of AIGs, where structurally identical nodes are merged
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Composition vs. expansion
[] Consider simplifying (x,1) in (x,0) (x,1) using (x,0) as don’t carecare onset (x,1) (x,0) care offset (x,1) (x,0)
In contrast to f withcare onset (x,1) (x,0) care offset (x,0) (x,1)
For existential quantification, composition can be much better than expansion for sparse (due to simple interpolants)
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Composition vs. expansion
[] Consider simplifying (x,1) in (x,0) (x,1) using (x,0) as don’t carecare onset (x,1) (x,0) care offset (x,1) (x,0)
In contrast to f withcare onset (x,1) (x,0) care offset (x,0) (x,1)
For universal quantification, composition can be much better than expansion for dense (due to simple interpolants)
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Generalization to predicate logic
For a language L in predicate logic under structure (interpretation) I, |=I x(y (x,y) = F (x,Fx))
QE is possible if such function F is finitely expressible in the language
If y (x,y) = (x,fx), then (a,b)y (a,y) is satisfied for any a, b with f(a)=b
If for any a, b with f(a)=b satisfies (a,b)y (a,y), then
y (x,y) = (i (x,fix)), where f = fi if i holds {(a,b) | (a,b)y (a,y)} characterizes the flexibility of f,
which can be exploited to simplify QE
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Generalization to predicate logic
Examplex(ax2+c=0) over the real number
f(a,c) = (–c/a)1/2 if c/a 0 – if c/a > 0
Taking f(a,c) = (((–c/a)2)1/2)1/2, this quantified formula is equivalent to a((((–c/a)2)1/2)1/2)2+c=0
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Experiments
Given a sequential circuit, we compute its transition relation with input variables being quantified out, i.e.,
x [i (si' i(x,s))]
Simple quantification scheduling appliedAIG minimization applied
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Experimental results
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Discussion
Expansion vs. composition based QEAnalogy with two-level vs. multi-level circuit
minimizationRelaxing level constraints admits more compact
circuit representation
Sparsity may play an essential role in the effectiveness of composition-based QE
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Conclusions
Quantifier elimination with functional composition can be effective at least for some applications (where the sparsity condition holds)
Future workFind more applicationsQE in predicate logic
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Thanks for your attention!
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Questions?